Use HTTP Basic Auth for MLflow authentication
Changed MLflow authentication to use HTTP Basic Auth by embedding credentials in the tracking URI (https://user:pass@host). This is the standard authentication method for MLflow when using basic auth, rather than relying on environment variables alone. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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@ -13,14 +13,25 @@ from sklearn.ensemble import RandomForestClassifier
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from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, roc_auc_score
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import pandas as pd
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# Configure MLflow
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mlflow.set_tracking_uri(os.getenv("MLFLOW_TRACKING_URI", "https://mlflow.sortifal.dev"))
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# Configure MLflow with authentication
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tracking_uri = os.getenv("MLFLOW_TRACKING_URI", "https://mlflow.sortifal.dev")
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username = os.getenv("MLFLOW_TRACKING_USERNAME")
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password = os.getenv("MLFLOW_TRACKING_PASSWORD")
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# Set MLflow credentials from environment variables
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if os.getenv("MLFLOW_TRACKING_USERNAME") and os.getenv("MLFLOW_TRACKING_PASSWORD"):
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os.environ["MLFLOW_TRACKING_USERNAME"] = os.getenv("MLFLOW_TRACKING_USERNAME")
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os.environ["MLFLOW_TRACKING_PASSWORD"] = os.getenv("MLFLOW_TRACKING_PASSWORD")
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print("MLflow credentials configured from environment variables")
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# Build authenticated URI if credentials are provided
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if username and password:
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# Extract protocol and host from URI
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if tracking_uri.startswith("https://"):
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auth_uri = f"https://{username}:{password}@{tracking_uri[8:]}"
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elif tracking_uri.startswith("http://"):
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auth_uri = f"http://{username}:{password}@{tracking_uri[7:]}"
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else:
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auth_uri = tracking_uri
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mlflow.set_tracking_uri(auth_uri)
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print(f"MLflow credentials configured for {tracking_uri}")
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else:
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mlflow.set_tracking_uri(tracking_uri)
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print("MLflow configured without authentication")
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# Try to set experiment, but handle auth errors gracefully
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USE_MLFLOW = True
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